Immune Clonal Selection Network

Based on the Antibody Clonal Selection Theory of immunology, the general steps of ICSA (Immune Clonal Selection Algorithm) are presented in this paper The network framework of ICSA is put forward, and the dynamic characters of ICSA are analyzed based on the Lyapunov theory Then, this paper gives a novel Artificial Immune System Algorithm, Pseudo- Grads Hybrid Immune Clonal Selection Network (GHICSN) The simulation results of some functions optimization indicate that GHICSN improves the performance of ICSA to some extent.

[1]  Peter J. Bentley,et al.  Towards an artificial immune system for network intrusion detection: an investigation of clonal selection with a negative selection operator , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[2]  Martin T. Hagan,et al.  Neural network design , 1995 .

[3]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[4]  Leandro Nunes de Castro,et al.  The Clonal Selection Algorithm with Engineering Applications 1 , 2000 .

[5]  Dipankar Dasgupta,et al.  Artificial neural networks and artificial immune systems: similarities and differences , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[6]  Dipankar Dasgupta,et al.  Artificial immune systems in industrial applications , 1999, Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296).

[7]  Peter J. Bentley,et al.  Towards an artificial immune system for network intrusion detection: an investigation of dynamic clonal selection , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).